Black and orange coloration predict success during male–male competition in the guppy
Bibliographic record
Abstract
Abstract Investigating how intrasexual competition and intersexual mate choice act within a system is crucial to understanding the maintenance and diversity of sexually-dimorphic traits. These two processes can act in concert by selecting for the same trait, or in opposition by selecting for different extremes of the same trait; they can also act on different traits, potentially increasing trait complexity. We asked whether male–male competition and female mate choice act on the same male traits using Trinidadian guppies, which exhibit sexual size dimorphism and male-limited color patterns consisting of different colors arranged along the body and fins. We used behavioral assays to assess the relationship between color and competitive success and then compared our results to the plethora of data on female choice and color in our study population. Males initiated more contests if they were larger than their competitor. Males won contests more often if they had more black coloration than their competitor, and the effect of black was stronger when males had less orange than their competitor. Additionally, males won more often if they had either more structural color (iridescence) and more orange, or less structural color and less orange than their competitor, suggesting multiple combinations of color traits predict success. Females from our study population exhibit a strong preference for more orange coloration. Thus, traits favored in male contests differ from those favored by intersexual selection in this population. These results suggest that inter- and intrasexual selection, when acting concurrently, can promote increased complexity of sexually selected traits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".